Combined energy detection and one-order cyclostationary feature detection techniques in cognitive radio systems

One of the main requirements of cognitive radio systems is the ability to detect the presence of the primary user with fast speed and precise accuracy. To achieve that, a possible two-stage spectrum sensing scheme is suggested in this paper. More specifically, a fast spectrum sensing algorithm based on the energy detection is introduced focusing on the coarse detection. A complementary fine spectrum sensing algorithm adopts one-order cyclostationary properties of primary user＇s signals in time domain. Since the one-order feature detection is performed in time domain, the real-time operation and low-computational complexity can be achieved. Also, it drastically reduces hardware burdens and power consumption as opposed to two-order feature detection. The sensing performance of the proposed method is studied and the analytical performance results are given. The results indicate that better performance can be achieved in proposed two-stage sensing detection compared to the conventional energy detector.

An Improved Cyclostationary Feature Detection Based on the Selection of Optimal Parameter in Cognitive Radios

Spectrum sensing is an important part of cognitive radio systems to find spectrum hole for transmission which enables cognitive radio systems coexist with the authorized radio systems without harmful interference.In this paper,an improved cyclostationary feature detection method is proposed to reduce computational complexity without loss of good performance based on the optimal parameter selection strategy for choosing detection parameters of cyclic frequency and lag.Taking binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals as examples,the theoretical analyses are presented for choosing the optimal parameters.Simulation results are given to certify the correctness of the proposed parameter selection strategy and show the performance of the proposed method.

Fragmental Weight-Conservation Combining Scheme for Statistical Signal Transmissions under Fast Time-Varying Channels

Statistical Signal Transmission(SST)is a technique based on orthogonal frequency-division multiplexing(OFDM)and adopts cyclostationary features,which can transmit extra information without additional bandwidth.However,the more complicated environment in 5G communication systems,especially the fast time-varying scenarios,will dramatically degrade the performance of the SST.In this paper,we propose a fragmental weight-conservation combining(FWCC)scheme for SST,to overcome its performance degradation under fast time-varying channels.The proposed FWCC scheme consists of three phases:1、incise the received OFDM stream into pieces;2、endue different weights for fine and contaminated pieces,respectively;3、combine cyclic autocorrelation function energies of all the pieces;and 4、compute the final feature and demodulate data of SST.Through these procedures above,the detection accuracy of SST will be theoretically refined under fast time-varying channels.Such an inference is confirmed through numerical results in this paper.It is demonstrated that the BER performance of proposed scheme outperforms that of the original scheme both in ideal channel estimation conditions and in imperfect channel estimation conditions.In addition,we also find the experiential optimal weight distribution strategy for the proposed FWCC scheme,which facilitates practical applications.

A Selection Scheme for Optimum Number of Cooperative Secondary Users in Spectrum Sensing

An optimization scheme for choosing the optimum number of secondary users in cooperative spectrum sensing based on the cyclostationary feature detection with Neyman-Pearson criterion is proposed in this paper.The optimal soft combination test statistic for the cooperative spectrum sensing based on cyclostationary feature detection is derived according to the generalized likelihood ratio test and its corresponding detection performance is deduced.A target function,considering two important parameters as the resource use efficiency and the number of samples employed by each cooperative secondary user in the system design,is constructed to obtain the optimum number of cooperative secondary users.It can be found that the selection scheme is to make a tradeoff between the system complexity of the cognitive radio network and the global sensing performance of the cooperative spectrum sensing.